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Quality Of Experience-Based Image Feature Selection For Mobile Augmented Reality Applications, Yi Cao, Christian H. Ritz, Raad Raad
Quality Of Experience-Based Image Feature Selection For Mobile Augmented Reality Applications, Yi Cao, Christian H. Ritz, Raad Raad
Faculty of Engineering and Information Sciences - Papers: Part A
Mobile augmented reality applications rely on automatically recognising a visual scene through matching of derived image features. To ensure the Quality of Experience (QoE) perceived by users, such applications should achieve high matching accuracy meanwhile minimizing the waiting time to meet real-time requirement. An efficient solution is to develop an effective feature selection method to select the most robust features against distortions caused by camera capture to achieve high matching accuracy whilst transmission and matching process of the features are significant reduced. Feature selection is also beneficial to reducing the computational complexities of the matching system so that waiting time …
Adaptive And Robust Feature Selection For Low Bitrate Mobile Augmented Reality Applications, Yi Cao, Christian H. Ritz, Raad Raad
Adaptive And Robust Feature Selection For Low Bitrate Mobile Augmented Reality Applications, Yi Cao, Christian H. Ritz, Raad Raad
Faculty of Engineering and Information Sciences - Papers: Part A
Mobile augmented reality applications rely on automatically matching a captured visual scene to an image in a database. This is typically achieved by deriving a set of features for the captured image, transmitting them through a network and then matching with features derived for a database of reference images. A fundamental problem is to select as few and robust features as possible such that the matching accuracy is invariant to distortions caused by camera capture whilst minimising the bit rate required for their transmission. In this paper, novel feature selection methods are proposed, based on the entropy of the image …